**4. Remarks for future clinical research: the role of bioinformatics and immunoinformatics**

Immunological investigations are defined with the help of the generation of rapidly piling quantities of information, that is backed via genetics and proteomics projects and large-scale evaluation of pathogen- and antigen and host reactions. The need to store, handle and evaluate this quickly expanding source of biological, clinical as well as epidemiological information led to the conception of the field known as computational immunology or Immunoinformatics. Immunoinformatics employs computerized approaches or sources that can be utilized in the exploring of immune system actions. This field resides at the crossroad of experimental and computer sciences and utilizes domain-exclusive databanks, computer simulations, and approaches drawn from artificial intelligence. For instance, computational or artificial intelligence simulations are rapidly being utilized in order to trigger as well as enhance scientists' comprehension of immunity patterns, including antigen modification and antigen-presenting, and for assessment of host and pathogenic genomes [117].

Immunoinformatics has been utilized to shift the immune profile by designing immunogenic candidates which implement various epitopes that play a role in disease. We suggest that a pipeline should be developed to identify differentially expressed genes and biomarkers by Bioinformatics [118, 119] and shift the immune system via Immunoinformatics/in silico efforts (e.g., reverse vaccinology) [120–122]. Moreover, Bioinformatics can help to recognize plausible therapeutic targets by the detection of differentially expressed genes [123].

*Lupus and the Nervous System: A Neuroimmunoloigcal Update on Pathogenesis and Management… DOI: http://dx.doi.org/10.5772/intechopen.107970*

There is no definitive treatment for COVID-19 and vaccines, despite bringing major success, have failed to completely eradicate the disease and have side effects [124, 125].

In addition, guideline makers should take into account the influence of the current Coronavirus disease-2019 (COVID-19) pandemic on SLE and its CNS involvements, which are well-known [126]. A study showed that COVID-19 morbidity could be moderately raised in most SLE cases, even though restricted data can be inferred on more critical patients [127].

Cytokines and hyperinflammatory responses are common features of COVID-19 and SLE [128, 129]. Inflammasomes are valuable therapeutic targets that are implicated in a wide range of disorders, such as neuropsychiatric and neurodegenerative diseases [130], eye disorders [131], cardiovascular disorders, and others [132]. Inflammasomes have also been shown to be involved in SLE. Induction of the inflammasome, a multimeric complex that triggers caspase-1. After that, the cytokines IL-1β and IL-18 mature, which are key to SLE pathogenesis [133].

Finally, we suggest that novel antibodies other than classical factors included in SLE criteria are developed. For instance, autoantibodies to the δ-Opioid Receptor act as opioid inducers and exhibit immunomodulatory function. Anti-DOR autoantibodies may function to stimulate the cell-mediated/Th1 arm. In SLE patients, therefore, elevated levels of anti-MOR Abs could worsen the disease, whereas increasing the anti-DOR autoantibodies could aid to deviate to Th1-type immune feedback [134, 135].

#### **5. Conclusions**

Research efforts have characterized NPSLE and SLE. The significance of NPSLE, in particular, has been underrated as it affects a great portion of SLE cases. More studies should aim the development of novel treatments because, despite clinical experiment, none of the laboratory or neuroimaging biomarkers for diagnosing NPSLE have been found accurate or reliable in clinical practice. New biomarkers may enable clinicians to make a more objective assessment of patients' conditions. NPSLE therapy and management may be complicated at different phases. These difficulties are assigning patients to SLE, diagnosis based on vague presentations, and the restrictions and imprecise currently available therapy armamentarium. Development of treatments for SLE could be facilitated via Immunoinformatics/*in silico* technology to engineer and evaluate candidates rapidly. Finally, we believe the next-generation combinational therapeutic regimen should be tested to enable major advancements.

#### **Acknowledgements**

We thank the members of USERN MUBabol Office for their support.

## **Conflict of interest**

The authors declare no conflict of interest.

### **Notes/thanks/other declarations**

None.
